A programmable microfluidic cell array for combinatorial drug screening

We describe the development of a fully automatic and programmable microfluidic cell culture array that integrates on-chip generation of drug concentrations and pair-wise combinations with parallel culture of cells for drug candidate screening applications. The device has 64 individually addressable cell culture chambers in which cells can be cultured and exposed either sequentially or simultaneously to 64 pair-wise concentration combinations of two drugs. For sequential exposure, a simple microfluidic diffusive mixer is used to generate different concentrations of drugs from two inputs. For generation of 64 pair-wise combinations from two drug inputs, a novel time dependent variable concentration scheme is used in conjunction with the simple diffusive mixer to generate the desired combinations without the need for complex multi-layer structures or continuous medium perfusion. The generation of drug combinations and exposure to specific cell culture chambers are controlled using a LabVIEW interface capable of automatically running a multi-day drug screening experiment. Our cell array does not require continuous perfusion for keeping cells exposed to concentration gradients, minimizing the amount of drug used per experiment, and cells cultured in the chamber are not exposed to significant shear stress continuously. The utility of this platform is demonstrated for inducing loss of viability of PC3 prostate cancer cells using combinations of either doxorubicin or mitoxantrone with TRAIL (TNF-alpha Related Apoptosis Inducing Ligand) either in a sequential or simultaneous format. Our results demonstrate that the device can capture the synergy between different sensitizer drugs and TRAIL and demonstrate the potential of the microfluidic cell array for screening and optimizing combinatorial drug treatments for cancer therapy.     

Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models

African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic consequences for global food security. Recent studies have found a few antiviral agents that can inhibit ASFV infections. However, currently, there are no vaccines or antiviral drugs. Hence, there is an urgent need to identify new drugs to treat ASFV. Based on the structural information data on the targets of ASFV, we used molecular docking and machine learning models to identify novel antiviral agents. We confirmed that compounds with high affinity present in the region of interest belonged to subsets in the chemical space using principal component analysis and k-means clustering in molecular docking studies of FDA-approved drugs. These methods predicted pentagastrin as a potential antiviral drug against ASFVs. Finally, it was also observed that the compound had an inhibitory effect on AsfvPolX activity. Results from the present study suggest that molecular docking and machine learning models can play an important role in identifying potential antiviral drugs against ASFVs.     

An insight to the molecular interactions of the FDA approved HIV PR drugs against L38L↑N↑L PR mutant

The aspartate protease of the human immune deficiency type-1 virus (HIV-1) has become a crucial antiviral target in which many useful antiretroviral inhibitors have been developed. However, it seems the emergence of new HIV-1 PR mutations enhances drug resistance, hence, the available FDA approved drugs show less activity towards the protease. A mutation and insertion designated L38L↑N↑L PR was recently reported from subtype of C-SA HIV-1. An integrated two-layered ONIOM (QM:MM) method was employed in this study to examine the binding affinities of the nine HIV PR inhibitors against this mutant. The computed binding free energies as well as experimental data revealed a reduced inhibitory activity towards the L38L↑N↑L PR in comparison with subtype C-SA HIV-1 PR. This observation suggests that the insertion and mutations significantly affect the binding affinities or characteristics of the HIV PIs and/or parent PR. The same trend for the computational binding free energies was observed for eight of the nine inhibitors with respect to the experimental binding free energies. The outcome of this study shows that ONIOM method can be used as a reliable computational approach to rationalize lead compounds against specific targets. The nature of the intermolecular interactions in terms of the host–guest hydrogen bond interactions is discussed using the atoms in molecules (AIM) analysis. Natural bond orbital analysis was also used to determine the extent of charge transfer between the QM region of the L38L↑N↑L PR enzyme and FDA approved drugs. AIM analysis showed that the interaction between the QM region of the L38L↑N↑L PR and FDA approved drugs are electrostatic dominant, the bond stability computed from the NBO analysis supports the results from the AIM application. Future studies will focus on the improvement of the computational model by considering explicit water molecules in the active pocket. We believe that this approach has the potential to provide information that will aid in the design of much improved HIV-1 PR antiviral drugs.     

InfVis--platform-independent visual data mining of multidimensional chemical data sets

The tremendous increase of chemical data sets, both in size and number, and the simultaneous desire to speed up the drug discovery process has resulted in an increasing need for a new generation of computational tools that assist in the extraction of information from data and allow for rapid and in-depth data mining. During recent years, visual data mining has become an important tool within the life sciences and drug discovery area with the potential to help avoiding data analysis from turning into a bottleneck. In this paper, we present InfVis, a platform-independent visual data mining tool for chemists, who usually only have little experience with classical data mining tools, for the visualization, exploration, and analysis of multivariate data sets. InfVis represents multidimensional data sets by using intuitive 3D glyph information visualization techniques. Interactive and dynamic tools such as dynamic query devices allow real-time, interactive data set manipulations and support the user in the identification of relationships and patterns. InfVis has been implemented in Java and Java3D and can be run on a broad range of platforms and operating systems. It can also be embedded as an applet in Web-based interfaces. We will present in this paper examples detailing the analysis of a reaction database that demonstrate how InfVis assists chemists in identifying and extracting hidden information.     

Phage display of combinatorial peptide libraries: application to antiviral research

Given the growing number of diseases caused by emerging or endemic viruses, original strategies are urgently required: (1) for the identification of new drugs active against new viruses and (2) to deal with viral mutants in which resistance to existing antiviral molecules has been selected. In this context, antiviral peptides constitute a promising area for disease prevention and treatment. The identification and development of these inhibitory peptides require the high-throughput screening of combinatorial libraries. Phage-display is a powerful technique for selecting unique molecules with selective affinity for a specific target from highly diverse combinatorial libraries. In the last 15 years, the use of this technique for antiviral purposes and for the isolation of candidate inhibitory peptides in drug discovery has been explored. We present here a review of the use of phage display in antiviral research and drug discovery, with a discussion of optimized strategies combining the strong screening potential of this technique with complementary rational approaches for identification of the best target. By combining such approaches, it should be possible to maximize the selection of molecules with strong antiviral potential.     

Bioactivity and molecular docking of synthesized macromolecular ligand and its complex

The development of drug resistant strains of the pathogenic fungi despite the availability of large number of drugs demands the development of new and more potential drug molecules. Dendrimer based drug molecules are comparatively less researched upon and a recent advancement in this field. The present study is concerned with the preparation of macromolecular ligand and its complex using ethylenediamine and methylmethacrylate as starting material. The reaction goes via Michael addition reaction and synthesized dendritic units were used as ligands to obtain metal-ligand complexes. Obtained ligand and its complex were characterized in terms of different techniques such as FTIR, ¹H NMR, ESI-MS, UV–Vis and Elemental analysis. Further, the ligand and its complex were used to determine antifungal activity against C. albicans ATCC 90028 by MICs and Disk diffusion assay. Comet assay and Molecular docking techniques were used to show toxicity effects and ligand–DNA interactions respectively. Ligand and its complex were obtained in very good yield with square planar geometry and having good antifungal potential against C. albicans. It was also found from Molecular docking and Comet assay, that the Copper complex interacts strongly with DNA and shows less toxicity than ligand. The compounds can serve as promising leads for the development of new antifungal agents.     

pK<Subscript>a</Subscript> based protonation states and microspecies for protein–ligand docking

In this paper we present our reworked approach to generate ligand protonation states with our structure preparation tool SPORES (Structure PrOtonation and REcognition System). SPORES can be used for the preprocessing of proteins and protein–ligand complexes as e.g. taken from the Protein Data Bank as well as for the setup of 3D ligand databases. It automatically assigns atom and bond types, generates different protonation, tautomeric states as well as different stereoisomers. In the revised version, pKa calculations with the ChemAxon software MARVIN are used either to determine the likeliness of a combinatorial generated protonation state or to determine the titrable atoms used in the combinatorial approach. Additionally, the MARVIN software is used to predict microspecies distributions of ligand molecules. Docking studies were performed with our recently introduced program PLANTS (Protein–Ligand ANT System) on all protomers resulting from the three different selection methods for the well established CCDC/ASTEX clean data set demonstrating the usefulness of especially the latter approach.     

Racemates versus enantiomerically pure drugs: putting high-performance liquid chromatography to work in the selection process

In view of the current negative attitude towards pharmaceutical preparations containing two or more drug substances, it is not surprising that the stereoisomeric composition of drugs has become a key issue in their development, regulatory approval and marketing. As the requirements placed on the purity of drugs become more and more stringent, the question arises of whether a racemic mixture should be automatically considered as being 50% impure. The answer is complex and requires careful comparative evaluations of the activities, toxicities and pharmacokinetics of the two enantiomers. In addition to the risk-benefit factors, the cost-benefit factors should also be carefully weighed in order to reach a decision which will guarantee drug safety. Excessive development costs and an unnecessary regulatory burden resulting from systematic demands for enantiomerically homogeneous drugs can be avoided with very potent drugs administered at low dosages and low-potency drugs for which the "inactive" isomer is not considerably more toxic than the active isomer. Regardless of the final decision taken, during the preclinical and clinical drug development it is important to have analytical methods suitable for conducting pertinent studies. This paper discusses the importance of stereochemistry in drug development and the role of high-performance liquid chromatography as a pre-eminent tool for analytical and preparative enantioselective separations.     

yaInChI: modified InChI string scheme for line notation of chemical structures

A modified InChI (International Chemical Identifier) string scheme, yaInChI (yet another InChI), is suggested as a method for including the structural information of a given molecule, making it straightforward and more easily readable. The yaInChI theme is applicable for checking the structural identity with higher sensitivity and generating three-dimensional (3-D) structures from the one-dimensional (1-D) string with less ambiguity than the general InChI method. The modifications to yaInChI provide non-rotatable single bonds, stereochemistry of organometallic compounds, allene and cumulene, and parity of atoms with a lone pair. Additionally, yaInChI better preserves the original information of the given input file (SDF) using the protonation information, hydrogen count +1, and original bond type, which are not considered or restrictively considered in InChI and SMILES. When yaInChI is used to perform a duplication check on a 3D chemical structure database, Ligand.Info, it shows more discriminating power than InChI. The structural information provided by yaInChI is in a compact format, making it a promising solution for handling large chemical structure databases.     

Selected Thoughts on Hydrophobicity in Drug Design

The fundamental aim of drug design in research and development is to invent molecules with selective affinity towards desired disease-associated targets. At the atomic loci of binding surfaces, systematic structural variations can define affinities between drug candidates and biomolecules, and thereby guide the optimization of safety, efficacy and pharmacologic properties. Hydrophobic interaction between biomolecules and drugs is integral to binding affinity and specificity. Examples of antiviral drug discovery are discussed.     

CHARMM‐GUI ligand reader and modeler for CHARMM force field generation of small molecules

Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM‐GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM‐GUI modules to build a protein‐ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM‐GUI at http://www.charmm-gui.org/input/ligandrm . © 2017 Wiley Periodicals, Inc.     

Radiolabeling of low molecular weight d-galactose-based glycodendrimer with technetium-99m and biodistribution studies

Glycodendrimers are neoglycoconjugates that can be considered as bioisosters of glycoproteins, since they can mimic the multivalent interactions of lectin-carbohydrate. The ability of glycodendrimers to present multivalent interactions with lectins as compared to a monovalent ligand is referred to as “cluster effect”. It is expected that, because of the cluster effect, glycodendrimers would result in a better association with lectins than mono-carbohydrate anchored systems. Radioisotopes are useful to evaluate biodistribution of molecules. This study is important to obtain information about molecule–receptor interactions. Indeed, such study can provide an exquisite tool to evaluate the affinity of certain molecules to specific areas in the body, leading to the development of new radiopharmaceuticals and/or drug delivery systems. Herein, we describe a d-galactose coated low molecular weight PAMAM G0 dendrimer that was successfully radiolabeled with technetium-99m. Biodistribution studies and scintigraphic images were performed in healthy mice. It was observed high liver uptake which was significantly reduced in blocking studies, indicating hepatic specificity. Therefore, low molecular weight glycodendrimer can be considered as useful platform for selective targeting of drugs to the liver and to assess hepatic function.     

Biosynthetic studies and genetic engineering of pactamycin analogs with improved selectivity toward malarial parasites

Pactamycin, one of the most densely functionalized aminocyclitol antibiotics, has pronounced antibacterial, antitumor, antiviral, and antiplasmodial activities, but its development as a clinical drug was hampered by its broad cytotoxicity. Efforts to modulate the biological activity by structural modifications using synthetic organic chemistry have been difficult because of the complexity of its chemical structure. However, through extensive biosynthetic studies and genetic engineering, we were able to produce analogs of pactamycin that show potent antimalarial activity, but lack significant antibacterial activity, and are about 10-30 times less toxic than pactamycin toward mammalian cells. The results suggest that distinct ribosomal binding selectivity or new mechanism(s) of action may be involved in their plasmodial growth inhibition, which may lead to the discovery of new antimalarial drugs and identification of new molecular targets within malarial parasites.     

Novel Methods of Enhanced Retention in and Rapid, Targeted Release from Liposomes

Liposomes are single bilayer capsules with distinct interior compartments in which hydrophilic drugs, imaging agents, diagnostics, etc. can be sequestered from the exterior environment. The polar parts of the individual lipids face the water compartments, while the hydrophobic parts of the lipid provide a barrier in which hydrophilic or charged molecules are poorly soluble. Hydrophobic molecules can be dissolved within the bilayer. The bilayers are typically from 3 - 6 nm thick and the liposome can range from about 50 nm - 50 microns in diameter. The question asked in this review is if any one bilayer, regardless of its composition, can provide the extended drug retention, long lifetime in the circulation, active targeting to specific tissues and rapid and controllable drug release at the site of interest. As an alternative, we review methods of self-assembling multicompartment lipid structures that provide enhanced drug retention in physiological environments. We also review methods of externally targeting and triggering drug release via the near infrared heating of gold nanoshells attached to or encapsulated within bilayer vesicles.     

Development and Effects of Influenza Antiviral Drugs

Influenza virus is a highly contagious zoonotic respiratory disease that causes seasonal outbreaks each year and unpredictable pandemics occasionally with high morbidity and mortality rates, posing a great threat to public health worldwide. Besides the limited effect of vaccines, the problem is exacerbated by the lack of drugs with strong antiviral activity against all flu strains. Currently, there are two classes of antiviral drugs available that are chemosynthetic and approved against influenza A virus for prophylactic and therapeutic treatment, but the appearance of drug-resistant virus strains is a serious issue that strikes at the core of influenza control. There is therefore an urgent need to develop new antiviral drugs. Many reports have shown that the development of novel bioactive plant extracts and microbial extracts has significant advantages in influenza treatment. This paper comprehensively reviews the development and effects of chemosynthetic drugs, plant extracts, and microbial extracts with influenza antiviral activity, hoping to provide some references for novel antiviral drug design and promising alternative candidates for further anti-influenza drug development.